Daily GTM Feed

Trust is the New Currency in B2B Buying: SurveyMonkey, Reddit

These are high % stats showing what we implicitly already know

• Peer validation (73% trust) now dramatically outweighs traditional vendor marketing (55% trust vendor sites, 39% trust AI chatbots, 36% trust social media) in early-stage B2B buying
• 83% of B2B buyers complete self-directed research before sales engagement, with high-stakes categories (software, professional services, HR) taking several weeks to months in extended evaluation
• Search engines serve as navigation layer, not destination—buyers use search to identify options then validate through peer communities like Reddit (121M daily users, 19% YoY growth), creating imperative for authentic community presence

Claude Channels

The move from user initiated to automated workflows is one of the main transitions with current agentic capabilities IMO

• Claude Channels (launched March 20, 2026) enables event-driven AI automation via MCP protocol, shifting from pull-based (user-initiated) to push-based (event-triggered) workflows
• Practical use case: CI/CD failures can trigger autonomous investigation, fix deployment, and resolution without human intervention - reducing 12-hour incident windows to near-zero
• Technical implementation uses MCP servers connecting Claude Code to messaging platforms (Telegram/Discord at launch), with Bun runtime for 4x faster cold-start performance vs Node

AWS Accelerates Internal AI Agents Following Staff Cuts

If you think white collar job displacement is a joke, or a distant future concern, this is just one more sign it is most definitely NOT. It's here.

• AWS is deploying AI agents to handle technical sales support functions previously performed by thousands of specialists
• The AI automation directly correlates with recent layoffs of hundreds in sales, business development, and technical specialist roles
• Major cloud provider is using its own AI capabilities to reduce headcount in customer-facing technical roles, signaling broader industry trend

AI News Weekly - 100 years from now : The Case for Artificial Stupidity - Mar 23rd 2026

now this is truly thought-provking

Why Hasn’t AI Made Work Easier?

• Large-scale study (164K workers, 180-day tracking) shows AI adoption doubled time spent on email/messaging/chat and increased business software use by 94%, but reduced focused work time by 9%
• This represents a 'productivity paradox'—AI accelerates shallow, context-switching work while cannibalizing the deep work that drives actual value creation
• Pattern repeats historical technology adoption cycles (email, mobile, video-conferencing) where efficiency tools paradoxically increased busyness without proportional output gains

Cursor admits its new coding model was built on top of Moonshot AI’s Kimi

• Cursor's new coding model is built on Chinese AI company Moonshot AI's Kimi foundation model
• This represents a significant supply chain transparency issue in a widely-adopted developer tool
• Geopolitical tensions around Chinese AI models create regulatory and compliance risk for enterprises using Cursor

Confronting the CEO of the AI company that impersonated me

• Grammarly/Superhuman shipped 'Expert Review' feature that cloned real journalists and experts as AI advisors without permission, triggering class action lawsuit
• Company response evolved from email opt-out to killing feature entirely after backlash - demonstrates reactive vs proactive approach to AI ethics
• Case illustrates emerging regulatory/legal risk category: AI companies using real people's professional identities and expertise as training data or product features without consent

Where Were YOU When the Revenue Multiples Died?

The GTM Engineer Pulse | #20

this is an interesting acquisition and consolidation, dont bet against apollo still

• GTM platform consolidation accelerating: Apollo acquiring Pocus signals aggressive upmarket push and category consolidation, with Apollo positioning as 'AI-native operating system for GTM teams from SMB to enterprise'
• AI agent infrastructure going 24/7: Anthropic's scheduled tasks for Claude Code enables always-on AI agents, backed by $100M ecosystem investment — fundamental shift from on-demand to autonomous GTM operations
• Terminal-native GTM emerging: Relevance AI's Programmatic GTM from terminal represents new paradigm where GTM operations become code-first, developer-driven workflows rather than UI-based point solutions

The bottleneck flipped: AI made execution fast and exposed everything around it that isn't

• AI compressed execution speed (weeks to hours for prototyping) but exposed coordination/decision-making as the new bottleneck - approval chains, planning cycles, and leadership velocity didn't accelerate
• 55% of CEOs who cut headcount citing AI already regret it; 42% of companies abandoned AI initiatives in 2025 (up from 17% prior year) - suggesting premature optimization and misdiagnosis of productivity gains
• Monday.com's counter-strategy: automated 100 SDRs but redeployed instead of cutting, recognizing 'every time we eliminate one bottleneck, a new one emerges' - treating AI as bottleneck-shifter not headcount-reducer

What Wins When Anyone Can Build Anything with Brett Queener, Partner at Bonfire Ventures

would echo field marketing is really the lifeblood now

• Traditional GTM competitive advantages (explanation, education, sales motion sophistication) are being commoditized by AI - 'right to win' now resets every 30 days
• Events creating 75%+ of pipeline for early-stage companies as face-to-face becomes critical when buyers bet careers on products that didn't exist 6 months ago
• Vertical software more defensible than horizontal platforms in AI era; Salesforce/HubSpot ecosystems risk becoming 'boat anchors' as agentic software collapses traditional sales motions from SDR to CSM

AI Native or Death. Choose.

Super useful and interesting — core AI-native thesis directly relevant to STEEPWORKS positioning. Victor flagged manually.

• AI-native companies show dramatically higher revenue per employee than traditional SaaS
• The AI-native label requires specific product characteristics, not just AI adoption
• Financial metrics reveal a clear performance gap between genuine AI-native ventures and AI-washed incumbents

Built an autonomous system where 5 AI models argue about geopolitical crisis outcomes: Here's what I learned about model behavior

• Multi-model consensus systems reveal significant disagreement (25+ points) between leading AI models on identical scenarios, with Grok showing bias toward OSINT signals
• Models anchor to their own previous outputs when shown historical context, requiring 'blind' operation to maintain independent reasoning
• Grounding/RAG prevents source hallucination but not content hallucination—models can fabricate specific data while correctly citing authoritative sources

Use subagents and custom agents in Codex

• OpenAI Codex launched subagents in general availability with default agents for 'explorer', 'worker', and 'default' - similar to Claude Code's implementation
• Custom agents can be defined as TOML files in ~/.codex/agents/ with custom instructions and specific model assignments (including gpt-5.3-codex-spark for speed)
• Subagents pattern has achieved cross-platform standardization - now supported by OpenAI Codex, Claude Code, Gemini CLI, Mistral Vibe, OpenCode, VS Code, and Cursor, signaling architectural convergence in AI coding tools

Gartner: 67% of B2B Buyers Prefer a Rep-Free Experience

This is the future. Even at high subscription $$$

• Two-thirds of B2B buyers now prefer rep-free buying experiences, with 45% already using AI in recent purchases—representing a fundamental shift from seller-led to buyer-led journeys
• Buyer confidence is the new revenue metric: confident buyers are 2x more likely to report high-quality deals, requiring sellers to deliver 'value clarity' (understanding how solution improves outcomes in buyer's specific context)
• Sales enablement must evolve from static content distribution to AI-driven, workflow-embedded support with modular, agent-ready content that serves both self-guided buyers and seller-assisted interactions

I turned my Claude Code agents into Tamagotchis so I can monitor them from tmux

Harness vs model debates continue

• Multi-agent AI coding workflows are becoming common enough to require dedicated orchestration tooling - developer built custom solution after existing tools (PixelHQ, VS Code plugin) didn't meet needs
• The 'Tamagotchi' metaphor reveals a shift in mental model: AI agents as persistent entities requiring monitoring and care, not just one-off tools
• Developer used Claude Code to build the monitoring tool for Claude Code agents (meta-development pattern) - built in Rust + Ratatui for tmux-native experience, suggesting preference for terminal-based workflows over GUI solutions

Google Just Did Something Most Companies Are Completely Missing

• Google launched managed MCP (Model Context Protocol) servers enabling AI agents to directly access Google Cloud services without custom integration maintenance
• This represents an infrastructure shift from brittle custom API integrations to enterprise-grade, standardized agent connectivity with built-in security and scalability
• The pattern repeats: early adopters build demos for attention, but infrastructure builders gain long-term leverage - MCP standardization signals where enterprise AI agent adoption is heading

Just passed the new Claude Certified Architect - Foundations (CCA-F) exam with a 985/1000!

• Anthropic launched first formal certification program (CCA-F) for Claude architects, signaling professionalization of AI implementation
• Exam focuses on practical skills: prompt engineering for tool use, context window management, and Human-in-the-Loop workflows
• Early adopter program suggests Anthropic building enterprise credentialing ecosystem to compete with established cloud vendors

The bottleneck flipped: AI made execution fast and exposed everything around it that isn't

It's so true, anything outside th CLI seems to move sooo slow

• AI compressed execution speed (weeks to hours for prototyping) but exposed coordination/decision-making as the new bottleneck - approval chains, planning cycles, and leadership velocity didn't accelerate
• 55% of CEOs who cut headcount citing AI already regret it; 42% of companies abandoned AI initiatives in 2025 (up from 17% prior year) - suggesting premature optimization and misdiagnosis of productivity gains
• Monday.com's counter-strategy: automated 100 SDRs but redeployed instead of cutting, recognizing 'every time we eliminate one bottleneck, a new one emerges' - treating AI as bottleneck-shifter not headcount-reducer

How to build MEDDICC scoring in Salesforce using Claude Code

• MEDDICC implementations fail not because of methodology flaws but because of implementation infrastructure gaps - specifically the 40-60 hour build burden that falls on RevOps teams without developer resources
• Claude Code + GitHub workflows enable RevOps practitioners to build and maintain complex Salesforce scoring systems without dedicated developers, collapsing implementation time and maintenance overhead
• The standard approach (custom fields + formula fields + manual validation) creates technical debt that compounds over 12 months until the initiative is abandoned - AI coding tools offer a path to sustainable implementation

I fed 14 years of daily journals into Claude Code

When you have pre-existing context AI is so powerful

• Individual processed 14 years (5,000 files) of personal journals through Claude Code, discovering AI's ability to identify patterns invisible to the author due to cognitive bias or self-criticism
• User developed iterative prompting strategy: started with specific perspectives (therapist, coach, relationships), then processed chronologically (month-by-month, year-by-year) to create longitudinal evolution report
• Practical framework shared via GitHub repo demonstrates emerging 'AI as mirror' use case - not for productivity but for self-insight extraction from existing unstructured personal data

From Figma to Claude Code and back | Gui Seiz & Alex Kern (Figma)

Visual design one of last frontiers so this an interesting read

• Figma's MCP enables bidirectional sync between design files and production code, eliminating static handoffs and version drift
• AI coding tools enable 90% code generation when codebase is properly structured, with custom skills automating pre-flight checks and CI monitoring
• Design workflow is bifurcating: AI handles rushed middle execution phase while humans focus on strategic planning (upstream) and quality craft (downstream)

26 FAQs about GTM Engineering in 2026

A good if high level overview

• Article is a FAQ format covering GTM Engineering predictions/practices for 2026
• Published by Brendan Short's The Signal newsletter (6,595+ subscribers)
• Content truncated - only intro/header visible, preventing full analysis

A guide to advanced B2B positioning

• Content is a podcast/video episode announcement, not substantive article
• Focuses on positioning fundamentals and cross-functional alignment challenges
• No specific case studies, metrics, or implementation details provided in excerpt

OpenAI's top exec resignation exposes something bigger than one Pentagon deal

• OpenAI's Pentagon deal reveals industry pattern of prioritizing capability deployment over governance readiness, with Kalinowski's resignation highlighting concerns about surveillance oversight and autonomous weapons authorization
• Market fragmentation emerging: OpenAI took contract immediately, Anthropic refused and got DoD blacklisted, creating divergent vendor positioning on defense AI that will impact enterprise procurement decisions
• Classified AI deployment presents fundamentally different engineering challenges (non-leaking data, auditable outputs, high-stakes accuracy) that most commercial AI vendors haven't solved, creating gap between contract signing and actual capability delivery

Open source persistent memory for AI agents — local embeddings, no external APIs

• Open-source alternative to commercial AI agent memory solutions using local embeddings (MiniLM-L6) instead of API-dependent services
• Simplifies infrastructure by using SQLite instead of dedicated vector databases, reducing deployment complexity
• Four-layer recall system (static facts + semantic + importance + recency) with auto-linking knowledge graph and built-in visualization

I classified 3.5M US patents with Nemotron 9B on a single RTX 5090 — then built a free search engine on top

• Local LLM (Nemotron 9B on RTX 5090) classified 3.5M patents in 48 hours, demonstrating consumer hardware can handle enterprise-scale classification tasks
• Contrarian architecture choice: FTS5 full-text search outperforms vector embeddings for domain-specific use cases requiring exact phrase matching and deterministic results
• Complete technical stack disclosed: SQLite FTS5 + local LLM query expansion + BM25 ranking with custom weights + FastAPI, hosted on Chromebook via Cloudflare Tunnel - proving production-grade search doesn't require cloud infrastructure

You Could Be Next

behind a paywall, but this is important

• White-collar workers displaced by AI (content marketing, copywriting) are being recruited to train the very models that replaced them, creating a cruel economic feedback loop
• AI training labor operates as precarious gig work with no job security - projects canceled with zero notice despite workers planning finances around the income ($45/hr but can disappear in 2 days)
• The AI training supply chain is deliberately opaque - workers don't know which AI they're training ('the client'), what it's for, or how their work fits into the larger system, preventing informed consent about contributing to further automation

A guide to advanced B2B positioning

super rich detail, not about AI. refreshing and expert practical content for early-stage: Disagreement about what to position against Product pessimism blinds the team to product strengths The differentiated value is poorly defined The company doesn’t know what they are positioning

• AI commoditization of product building shifts competitive advantage from development speed to distribution and positioning - the ability to cut through noise becomes paramount
• Strong positioning is the antidote to AI-driven product proliferation - specific, differentiated positioning helps products stand out in increasingly crowded markets
• Expert-led frameworks (April Dunford's 300+ company experience) provide battle-tested approaches to advanced B2B positioning challenges that teams commonly face

An Interview with Gregory Allen About Anthropic and the U.S. Government

• Content is interview format about Anthropic-government relations
• Focuses on policy/regulatory issues rather than practical implementation
• Lacks operational details, metrics, or actionable insights for GTM/productivity use cases